Mattsson Kauppi, Mona

Mörtvik, Gunnel

Abstract [en]

SMC is a research-institute that investigates the interaction between humans and the environment. Sometimes they construct interpolated surfaces to look for spatial patterns, for example, in the distribution or variance of personal income, educational status or deaths from cancer. These tasks require them to convert point-data into some sort of grid and compute statistics for the data within the cells. Our task was to look for optimal grid resolutions and to construct a variable grid that can be used to characterise different types of spatial patterns that shows the population density for Sweden. While trying to find the optimal grid-size we worked with regular and irregular grids looking at population density per square-metre in each grid-cell respectively the number of persons per grid-square. The regular grids were made with SQL-queries towards the database containing the information about the population. To present these grids a GIS-software, Arc View were used. Then the grids were interpolated to get a smoother surface and the best estimation for the population densities between the known points. Interpolation-methods used were IDW that uses a mean to calculate the value for the interpolated cell and spline, which fits a minimum-curvature surface through the points. To visualise the different densities within the grid-cells we used graduated colours and contour lines. We have also designed a program that uses a quad-tree structure to construct a variable grid where the grid-squares contain approximately the same number of observation. The program produces equivalent grids independently of the geographic location for the first split but there is a visual difference depending of what you set as the maximum number of people in each cell. Our conclusion was that it is difficult to find an optimal grid-size since the population density in Sweden is very skewed. The computer capacity and usage of the grid is also of great importance.